code: def step(self, action: np.ndarray) -> dm_env.TimeStep:
      self._steps_remaining -= 1
  
      observation = collections.OrderedDict()
      observation["obs1"] = np.full(
          (2,), self._steps_remaining, dtype=np.float32
      )
      observation["obs2"] = np.full(
          (3,), self._steps_remaining, dtype=np.float32
      )
  
      if self._steps_remaining < 1:
          return dm_env.TimeStep(
              step_type=dm_env.StepType.LAST,
              reward=-1.0,
              discount=0.0,  # Indicates a terminal state.
              observation=observation,
          )
      else:
          return dm_env.TimeStep(
              step_type=dm_env.StepType.MID,
              reward=0.0,
              discount=None,
              observation=observation,
          )
  
imports: import collections
  from typing import Callable, Mapping
  from unittest import mock
  from absl.testing import absltest
  from absl.testing import parameterized
  from dm_control import suite
  from dm_control.rl import control
  import dm_env
  from dm_env import specs
  from dopamine.labs.sac_from_pixels import deepmind_control_lib
  import numpy
label_desc: Use image node_id 5 for calling the MockDeepmindControlSuiteEnvironment obj's underlying member method code with example usage: obj.step(action) and returns: dm_env, dm_env